Knowledge modelling with the open source tool myCBR

Building knowledge intensive Case-Based Reasoning applications requires tools that support this on-going process between domain experts and knowledge engineers. In this paper we will introduce how the open source tool myCBR 3 allows for flexible knowledge elicitation and formalisation form CBR and non CBR experts. We detail on myCBR 3 's versatile approach to similarity modelling and will give an overview of the Knowledge Engineering workbench, providing the tools for the modelling process. We underline our presentation with three case studies of knowledge modelling for technical diagnosis and recommendation systems using myCBR 3

Similarity Measure Development for Case-Based Reasoning- A Data-driven Approach

In this paper, we demonstrate a data-driven methodology for modelling the local similarity measures of various attributes in a dataset. We analyse the spread in the numerical attributes and estimate their distribution using polynomial function to showcase an approach for deriving strong initial value ranges of numerical attributes and use a non-overlapping distribution for categorical attributes such that the entire similarity range [0,1] is utilized. We use an open source dataset for demonstrating modelling and development of the similarity measures and will present a case-based reasoning (CBR) system that can be used to search for the most relevant similar cases

Approaches to the use of sensor data to improve classroom experience

quipping classrooms with inexpensive sensors can enable students and teachers with the opportunity to interact with the classroom in a smart way. In this paper an approach to acquiring contextual data from a classroom environment, using inexpensive sensors, is presented. We present our approach to formalising the usage data. Further we demonstrate how the data was used to model specific room usage situation as cases in a Case-based reasoning (CBR) system. The room usage data was than integrated in a room recommendations system, reasoning on the formalised usage data. We also detail on our on-going work to integrating the systems presented in this paper into our Smart University vision

Building case-based reasoning applications with myCBR and COLIBRI Studio

myCBR and COLIBRI Studio are two well-established opensource frameworks for building case-based reasoning (CBR) applications, though they follow different approaches and support different phases of the CBR application development. In a nutshell: Where myCBR supports its users in developing a knowledge model for representing cases, it more or less leaves the software developers alone when they try to develop an application that uses the generated knowledge model. COLIBRI Studio, on the other hand, is focused in the development of applications that use that knowledge model. As soon as you have a knowledge model COLIBRI Studio offers templates for a variety of application types and supports in generating its source code. This paper explains the strengths and weaknesses of both frameworks regarding the rapid development of CBR applications. It also shows how to use both of them in conjunction

A Step Towards an Intelligent Digital Training Management System (I-DTMS)

The U.S. Army Digital Training Management System (DTMS) is a web-based system designed to create a single point of entry for units to schedule unit training, manage training resources, and create schedules and master calendars for training. Currently, the U.S. Army uses DTMS to manage unit training and help commanders at each step of the training management process from planning and preparing to execute and assessing the training plans. This research aims to add intelligent features to DTMS through augmenting it with an intelligent decision support system (ITPSS) that utilizes artificial intelligence techniques (case-based reasoning, in particular) to determine if training guidance (either annual training guidance or doctrinal template) was implemented correctly. The proposed system should also help company commanders to refine their unit training plans after reviewing previous similar unit training plans recommended or retrieved by the ITPSS. This research demonstrates how case-based reasoning could improve the training plan development and approval process in DTMS, and questionnaire results support this analysis. It is worth noting that the focus of this research is on the applicability and plausibility of the proposed decision system, not on developing an interface between DTMS and DSS

A Comparative Study of Cognitive Systems for Learning

Learning is the modification of a behavioral tendency by experience. Memory and reasoning are the most important aspects for learning in humans; information is temporarily stored in the short-term memory and processed, compared with existing memories and stored in long-term memory, and can be re-used when needed. One way to describe an organized pattern of thought or behavior and the categories of information along with their relationships is by using schemas. A cognitive script is one form of a schema that evolves over multiple exposures to the same set of stimuli and/or repeated enactment of a particular behavior. This research aims to provide a comparative study between three cognitive systems/tools designed to allow learning, by using cognitive scripts representation. Since retrieving and re-using past experiences is the core of any learning process, the focus of this thesis is to examine the current existing cognitive systems and tools to evaluate their ability to retrieve past experiences. SOAR, myCBR and Pharaoh are three systems considered for this thesis. Linear and multi-branched cognitive scripts were considered in order to measure the capacity of those systems to allow learning using cognitive scripts representation. The results of this work show that SOAR, myCBR and Pharaoh took almost the same time to retrieve a set of similar cognitive scripts to a query script. However, SOAR was able to retrieve one similar script only, while myCBR and Pharaoh were able to retrieve multiple scripts. Pharaoh tops the other two system in its ability to handle multibranched scripts of different sizes and the way it considers context

Case acquisition from text: ontology-based information extraction with SCOOBIE for myCBR

myCBR is a freely available tool for rapid prototyping of similarity-based retrieval applications such as case-based product recommender systems. It provides easy-to-use model generation, data import, similarity modelling, explanation, and testing functionality together with comfortable graphical user interfaces. SCOOBIE is an ontology-based information extraction system, which uses symbolic background knowledge for extracting information from text. Extraction results depend on existing knowledge fragments. In this paper we show how to use SCOOBIE for generating cases from texts. More concrete we use ontologies of the Web of Data, published as so called Linked Data interlinked with myCBR’s case model. We present a way of formalising a case model as Linked Data ready ontology and connect it with other ontologies of the Web of Data in order to get richer cases

Two-phased knowledge formalisation for hydrometallurgical gold ore process recommendation and validation

This paper describes an approach to externalising and formalising expert knowledge involved in the design and evaluation of hydrometallurgical process chains for gold ore treatment. The objective was to create a case-based reasoning application for recommending and validating a treatment process of gold ores. We describe a twofold approach. Formalising human expert knowledge about gold mining situations enables the retrieval of similar mining contexts and respective process chains, based on prospection data gathered from a potential gold mining site. Secondly, empirical knowledge on hydrometallurgical treatments is formalised. This enabled us to evaluate and, where needed, redesign the process chain that was recommended by the first aspect of our approach. The main problems with formalisation of knowledge in the domain of gold ore refinement are the diversity and the amount of parameters used in literature and by experts to describe a mining context. We demonstrate how similarity knowledge was used to formalise literature knowledge. The evaluation of data gathered from experiments with an initial prototype workflow recommender, Auric Adviser, provides promising results

Extracting knowledge from web communities and linked data for case-based reasoning systems

Web communities and the Web 2.0 provide a huge amount of experiences and there has been a growing availability of Linked Open Data. Making experiences and data available as knowledge to be used in case-based reasoning CBR systems is a current research effort. The process of extracting such knowledge from the diverse data types used in web communities, to transform data obtained from Linked Data sources, and then formalising it for CBR, is not an easy task. In this paper, we present a prototype, the Knowledge Extraction Workbench KEWo, which supports the knowledge engineer in this task. We integrated the KEWo into the open-source case-based reasoning tool myCBR Workbench. We provide details on the abilities of the KEWo to extract vocabularies from Linked Data sources and generate taxonomies from Linked Data as well as from web community data in the form of semi-structured texts